Wireless communications systems of the future are likely to be driven by increasing usage of diverse bandwidth-hungry applications which require streaming voice, video and data on devices such as smart phones, handhelds and portable devices. Advances in signal processing, source coding, digital communications have allowed voice and video to be compressed and packaged as data. Multiple-Input and Multiple-Output (MIMO) systems, Advanced Antenna Systems (AAS), Multi-User Detection (MUD), and channel coding techniques such as Turbo and Low Density Parity Check (LDPC) codes have pushed system throughputs toward the information theoretical limit (the Shannon Capacity). However, even though such systems and smart signal processing techniques allow for more efficient information transmission schemes, a fundamental bottleneck remains. That bottleneck is access to the RF spectrum.
In more detail, it is generally believed that there is ample RF spectrum available to meet the global demand for voice, video and data. For instance, based on measurements of the average spectrum usage in multiple different markets, it has been found that more than 80% of the available spectrum is under-utilized. Most of the current spectrum has been allocated using a command and control licensing structure where a few selected entities are in charge of large swaths of spectrum, many of which are underutilized. The most relevant example is that of broadcast television (TV) spectrum where signals are normally transmitted over the air at VHF and UHF frequencies. In rural markets TV channels often go unused due to limited demand. In urban markets, the majority of people have started receiving their TV transmission either using cable or optical fiber. Many countries are making transition towards Digital TV (DTV) where signals occupy much smaller bandwidths as compared to their analog counterparts. These factors lead to large and increasing amounts of spectrum that are allocated to broadcast services, but are locally unused. This vacant spectrum may be opportunistically accessed to transmit broadband data in case it can be established that such a use causes no harmful interference to the allocated (incumbent) broadcast services.
Technology already exists to allow opportunistic usage of RF spectrum. Such opportunistic use of spectrum is often called Dynamic Spectrum Access (DSA). Programs such as the neXt Generation (XG) Communications have proven that DSA techniques can allow access to channels allocated to incumbent users without harmful interference to the incumbent. The concept of cognitive radio also seems to be feasible. Cognitive radios are defined as radios that are capable of sensing their surrounding environment and altering their transmission parameters to more optimally utilize the existing resources, such as RF spectrum, to meet current user needs. Some have even proposed combining DSA techniques with machine learning techniques to make better usage of the system resources while avoiding interference.
The future points to multitudes of such DSA enabled cognitive radio devices using a variety of different waveforms and protocols, co-existing, in cognitive networks to make the best possible use of the available spectrum. The word co-existence here is of importance since competing technologies will result in different types of waveforms and protocols being employed for various types of services. These diverse waveforms and protocols will need to share spectral resources without harming each other, hence the need for co-existence. Some of the Institute of Electrical and Electronics Engineers (IEEE) Standards working groups such as IEEE 802.15.2 have defined the term co-existence as the “ability of one system to perform a task in a given shared environment where other systems have an ability to perform their tasks and may or may not be using the same set of rules.”
The IEEE 802.22 standard is directed to wireless regional area networks (WRANs) that use white spaces (unused bandwidth) in the television broadcasting bands without interfering with other users. The standard is largely based on concepts underpinning the cognitive radio, which include spectrum sensing and management as well as spectrum mobility and sharing. Spectrum sensing and management generally involve the detection of the best spectrum to meet user quality of service (QoS) requirements and using it without harmful interference to other users. Spectrum mobility and sharing allow for maintaining seamless communications when transitioning from one spectrum to another (e.g., dynamic frequency selection, frequency hopping, etc), and strive for fairness in spectrum allocation (e.g., equal access).
To this end, cognitive radios and networks sharing common bandwidth have to effectively self-coexist with one another by accessing different parts of the available spectrum in an evenly or otherwise fairly distributed manner. Executing such self-coexistence is not trivial, and there are currently no available methods for resource allocation during situations requiring co-existence in cognitive radios. Moreover, conventional co-existence techniques require changes in the concept of communication system operation, thereby resulting in legacy systems not being inter-operable with systems requiring co-existence.
There is a need, therefore, for techniques that allow for resource allocation during situations requiring co-existence in cognitive radios.